Estimation of conditional average treatment effects on distributed data: A privacy-preserving approach

no code implementations • 5 Feb 2024 • Yuji Kawamata, Ryoki Motai, Yukihiko Okada, Akira Imakura, Tetsuya Sakurai

Second, our method enables collaborative estimation between different parties as well as multiple time points because the dimensionality-reduced intermediate representations can be accumulated.

Privacy Preserving

Collaborative causal inference on distributed data

no code implementations • 16 Aug 2022 • Yuji Kawamata, Ryoki Motai, Yukihiko Okada, Akira Imakura, Tetsuya Sakurai

Many existing methods for distributed data focus on resolving the lack of subjects (samples) and can only reduce random errors in estimating treatment effects.

Causal Inference Dimensionality Reduction